code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import requests
_snake_case : Optional[Any] = "YOUR API KEY"
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase = giphy_api_key ):
__snake_case : Optional[int] = "+".join(query.split() )
__snake_case : List[Any] ... | 81 |
'''simple docstring'''
def A ():
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def A (__lowerCamelCase :List[Any] ):
_lowerCAmelCase = 1
_lowerCAmelCase = 2
while i * i <= n:
_lowerCAmelCase = 0
while ... | 5 | 0 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers im... | 82 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 0 |
"""simple docstring"""
lowerCAmelCase__ = 0 # The first color of the flag.
lowerCAmelCase__ = 1 # The second color of the flag.
lowerCAmelCase__ = 2 # The third color of the flag.
lowerCAmelCase__ = (red, white, blue)
def ... | 83 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_... | 5 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class A_ :
'''simple docstring'''
def __init__( self ):
lowercase = ''
lowercase = ''
lowercase = []
lowercase = 0
lowercase = 256
lowercase ... | 84 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 0 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
SCREAMING_SNAKE_CASE__ : Any ... | 85 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__a :Any = ''
__a :int = ''
__a :str = ''
__a :Optional[Any] = 1 # (0 is vertical, 1 is horizontal)
def __snake_case ( ):
"""simple docstring"""
... | 86 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 5 | 0 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since... | 87 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMA... | 5 | 0 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def _snake_case ( __snake_case : str = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ... | 88 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 | 0 |
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
logging,
)
logging.set_v... | 89 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logge... | 5 | 0 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( A , A ) -> ... | 90 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 | 0 |
"""simple docstring"""
import os
def _snake_case ( ):
A = os.path.dirname(os.path.realpath(snake_case__ ) )
A = os.path.join(snake_case__ , 'triangle.txt' )
with open(snake_case__ ) as f:
A = f.readlines()
A = []
for line in triangle:
A = []
for number in lin... | 91 |
'''simple docstring'''
import functools
def A (__lowerCamelCase :list[int] , __lowerCamelCase :list[int] ):
# Validation
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or not all(isinstance(__lowerCamelCase , __lowerCamelCase ) for day in days )... | 5 | 0 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 92 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def A (__lowerCamelCase :List[Any] ):
_lowe... | 5 | 0 |
"""simple docstring"""
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( a ):
"""simple docstring"""
__magic_name__ :Union[str, Any] = (EulerDis... | 93 |
'''simple docstring'''
from itertools import product
def A (__lowerCamelCase :int , __lowerCamelCase :int ):
_lowerCAmelCase = sides_number
_lowerCAmelCase = max_face_number * dice_number
_lowerCAmelCase = [0] * (max_total + 1)
_lowerCAmelCase ... | 5 | 0 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import Batc... | 94 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _lowercase ( self ):
"""simple docstring"""
_lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
... | 5 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase_ = {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}
try:
if not is_torch_available():
... | 95 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowercase = False
try:
_lowerca... | 5 | 0 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__lowerCamelCase = '.'
if __name__ == "__main__":
__lowerCamelCase = os.path.join(REP... | 96 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 5 | 0 |
from abc import ABC, abstractmethod
from typing import List, Optional
class lowercase__( UpperCAmelCase ):
"""simple docstring"""
def __init__( self : str ) -> Optional[Any]:
# test for the above condition
self.test()
def _lowercase ( self : T... | 97 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transfo... | 5 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[str] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
... | 98 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 5 | 0 |
from __future__ import annotations
def a (lowerCAmelCase__ , lowerCAmelCase__ = None ):
__a = word_bank or []
# create a table
__a = len(lowerCAmelCase__ ) + 1
__a = []
for _ in range(lowerCAmelCase__ ):
table.append([] )
# seed value
__a... | 99 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : Tuple = (DDPMScheduler,)
def _lowercase... | 5 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requi... | 100 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
f... | 5 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
_UpperCAmelCase ... | 101 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-ba... | 5 | 0 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 1000 , SCREAMING_SNAKE_CASE = True ):
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
and isinstance(SCREAMING_SN... | 102 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Bl... | 5 | 0 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
snake_case = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, ... | 103 |
'''simple docstring'''
def A ():
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def A (__lowerCamelCase :List[Any] ):
_lowerCAmelCase = 1
_lowerCAmelCase = 2
while i * i <= n:
_lowerCAmelCase = 0
while ... | 5 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""KT""")
UpperCamelCase = TypeVar("""VT""")
class UpperCamelCase__ ( Generic[KT, VT] ):
"... | 104 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 0 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ : str = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake... | 105 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_... | 5 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable()
except... | 106 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 0 |
'''simple docstring'''
class lowercase_ :
"""simple docstring"""
def __init__( self : Tuple, UpperCamelCase__ : int ) -> None:
_A = size
_A = [0] * size
_A = [0] * size
@staticmethod
def __UpperCAmelCase ( UpperC... | 107 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
__a: List[Any] = 8.3_1_4_4_6_2 # Unit - J mol-1 K-1
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case , __snake_case ) -> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid inputs. Enter positive value.""" ... | 108 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 5 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
# See all GLPN models at https://huggingface.co/mod... | 109 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMA... | 5 | 0 |
"""simple docstring"""
from __future__ import annotations
import queue
class a :
def __init__( self , UpperCamelCase_ ):
UpperCAmelCase__ : int = data
UpperCAmelCase__ : Dict = None
UpperCAmelCase__ : Optional... | 110 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
lowercase ... | 211 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logge... | 5 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available... | 171 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 | 0 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from t... | 104 |
'''simple docstring'''
import functools
def A (__lowerCamelCase :list[int] , __lowerCamelCase :list[int] ):
# Validation
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or not all(isinstance(__lowerCamelCase , __lowerCamelCase ) for day in days )... | 5 | 0 |
from abc import ABC, abstractmethod
from typing import List, Optional
class _lowercase ( _SCREAMING_SNAKE_CASE ):
def __init__( self : Tuple ) -> Union[str, Any]:
"""simple docstring"""
self.test()
def UpperCamelCase ( self : Tuple ) -> D... | 203 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def A (__lowerCamelCase :List[Any] ):
_lowe... | 5 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, ge... | 631 |
'''simple docstring'''
from itertools import product
def A (__lowerCamelCase :int , __lowerCamelCase :int ):
_lowerCAmelCase = sides_number
_lowerCAmelCase = max_face_number * dice_number
_lowerCAmelCase = [0] * (max_total + 1)
_lowerCAmelCase ... | 5 | 0 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'The ... | 101 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _lowercase ( self ):
"""simple docstring"""
_lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
... | 5 | 0 |
def __UpperCamelCase ( _lowerCAmelCase = 10 , _lowerCAmelCase = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , __lowerCamelCase )
UpperCAmelCase = range(1 , __lowerCamelCase )
return sum(
1 for power in powers for base in bases if len(st... | 333 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowercase = False
try:
_lowerca... | 5 | 0 |
import math
import unittest
def A ( _lowerCamelCase ):
'''simple docstring'''
assert isinstance(__lowerCamelCase , __lowerCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
#... | 500 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 5 | 0 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_se... | 517 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transfo... | 5 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, lo... | 456 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 5 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : Tuple = (DDPMScheduler,)
def _lowercase... | 5 | 0 |
'''simple docstring'''
import os
from pathlib import Path
def __A ( ):
"""simple docstring"""
from torch.utils.cpp_extension import load
__SCREAMING_SNAKE_CASE : Dict = Path(__lowerCamelCase ).resolve().parent.parent.pare... | 211 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
f... | 5 | 0 |
from maths.prime_check import is_prime
def UpperCamelCase( __UpperCamelCase : int ):
if not isinstance(__lowerCamelCase ,__lowerCamelCase ):
lowerCAmelCase_ : Union[str, Any] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__lowerCame... | 171 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-ba... | 5 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int = 3, UpperCAmelCase_ : int = 7, UpperCAmelCase_ : int = 1000000 ) -> Dict:
"""simple docstring"""
A__ = 0
A__ = 1
for current_denomin... | 104 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Bl... | 5 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__lowercase = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SPEECHT5_PRETRAIN... | 203 |
'''simple docstring'''
def A ():
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def A (__lowerCamelCase :List[Any] ):
_lowerCAmelCase = 1
_lowerCAmelCase = 2
while i * i <= n:
_lowerCAmelCase = 0
while ... | 5 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}
try:
if not is_torch_available():
raise O... | 631 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 0 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 101 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_... | 5 | 0 |
from __future__ import annotations
from math import gcd
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase = 2 , _lowerCAmelCase = 1 , _lowerCAmelCase = 3 , ):
"""simple docstring"""
if num < 2:
raise ValueError("The input value cannot be less than 2" )
... | 333 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class UpperCAmelCase_ ( ... | 500 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers impo... | 517 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 5 | 0 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTester... | 456 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMA... | 5 | 0 |
"""simple docstring"""
def a ( ):
'''simple docstring'''
for n in range(1, 1000000 ):
yield n * (n + 1) // 2
def a ( __snake_case : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = 1
UpperCAmelCase_ ... | 608 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test... | 211 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logge... | 5 | 0 |
A__ : List[Any] = '''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
A__ : str = [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
A__ : ... | 171 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 | 0 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( UpperCAmelCase_ : list[int] ) -> List[str]:
"""simple docstring"""
return len(set(__lowerCamelCase ) ) == len(__lowerCamelCase )
if __name__ == "_... | 104 |
'''simple docstring'''
import functools
def A (__lowerCamelCase :list[int] , __lowerCamelCase :list[int] ):
# Validation
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or not all(isinstance(__lowerCamelCase , __lowerCamelCase ) for day in days )... | 5 | 0 |
def _lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
A_ = str(bin(__lowerCamelCase ) )[2:] # remove the leading "0b"
... | 203 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def A (__lowerCamelCase :List[Any] ):
_lowe... | 5 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP... | 631 |
'''simple docstring'''
from itertools import product
def A (__lowerCamelCase :int , __lowerCamelCase :int ):
_lowerCAmelCase = sides_number
_lowerCAmelCase = max_face_number * dice_number
_lowerCAmelCase = [0] * (max_total + 1)
_lowerCAmelCase ... | 5 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_di... | 101 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _lowercase ( self ):
"""simple docstring"""
_lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
... | 5 | 0 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch import nn
from ... | 333 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowercase = False
try:
_lowerca... | 5 | 0 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcessor,... | 500 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 5 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCamelCase__ ( a__ , a__ , a__ , a__ , a__ = None , a__ = None , a__ = None ... | 517 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transfo... | 5 | 0 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_utils... | 456 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 5 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCamelCase = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc... | 608 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : Tuple = (DDPMScheduler,)
def _lowercase... | 5 | 0 |
'''simple docstring'''
from collections.abc import Callable
def __A ( _SCREAMING_SNAKE_CASE : Callable[[float], float] , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float ):
"""simple docstring"""
__SCREAMING_SNA... | 211 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
f... | 5 | 0 |
from datetime import datetime
import requests
def UpperCamelCase( __UpperCamelCase : str ):
lowerCAmelCase_ : str = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
lowerCAmelCase_ : Union[str, Any] = requests.get(base_url + url ... | 171 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-ba... | 5 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMSc... | 104 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Bl... | 5 | 0 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
__lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
__lowercase = requests... | 203 |
'''simple docstring'''
def A ():
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def A (__lowerCamelCase :List[Any] ):
_lowerCAmelCase = 1
_lowerCAmelCase = 2
while i * i <= n:
_lowerCAmelCase = 0
while ... | 5 | 0 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}
class _UpperCAmelC... | 631 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 0 |
def a__ ( A__ ):
return sum(i for i in range(1, number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or not...')
lowerCAmelCase__ : Dict =int(input('Enter number: ').strip(... | 101 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_... | 5 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase =logging.get_logger(__name__)
__lowerCAmelCase ={
"kssteven/ibert-roberta-base": "https://huggingface.c... | 333 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
"configuration_time_series_transformer": [
"TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TimeSeriesTransformerConfig",
],
}
try:
... | 500 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils i... | 517 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 5 | 0 |
from __future__ import annotations
from collections.abc import Callable
A_ : Optional[Any] = list[list[float | int]]
def UpperCamelCase (lowercase_: Matrix , lowercase_: Matrix ) -> int:
A__ : str = len(__lowerCamelCase )
A__ : Optional[int] = ... | 456 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMA... | 5 | 0 |
"""simple docstring"""
import os
def a ( ):
'''simple docstring'''
with open(os.path.dirname(__lowerCamelCase ) + '''/p022_names.txt''' ) as file:
UpperCAmelCase_ :Tuple = str(file.readlines()[0] )
UpperCAmelCase_ :Any = names.replace(''... | 608 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
lowercase = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''enhancement''',
'''new pipeline/model''',
'''new scheduler''',
'''wip'... | 211 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logge... | 5 | 0 |
import pytest
A__ : List[str] = '''__dummy_dataset1__'''
A__ : List[str] = '''
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation... | 171 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=_SCREAMING_SNAKE_CASE )
class UpperCamelCase__ ( _SCREAMING_SNAKE_C... | 104 |
'''simple docstring'''
import functools
def A (__lowerCamelCase :list[int] , __lowerCamelCase :list[int] ):
# Validation
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or not all(isinstance(__lowerCamelCase , __lowerCamelCase ) for day in days )... | 5 | 0 |
from collections import defaultdict
def _lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A_ = first_str.lower().strip()
A_ = second_str.lower().strip()
# Remove whitespace
A_ =... | 203 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def A (__lowerCamelCase :List[Any] ):
_lowe... | 5 | 0 |
import os
def lowercase ( a = "input.txt" ):
'''simple docstring'''
with open(os.path.join(os.path.dirname(__lowerCamelCase ) , __lowerCamelCase ) ) as input_file:
SCREAMING_SNAKE_CASE_ :int = [
[int(__lowerCamelCase ) for element in line.split("," )]
for l... | 631 |
'''simple docstring'''
from itertools import product
def A (__lowerCamelCase :int , __lowerCamelCase :int ):
_lowerCAmelCase = sides_number
_lowerCAmelCase = max_face_number * dice_number
_lowerCAmelCase = [0] * (max_total + 1)
_lowerCAmelCase ... | 5 | 0 |
import math
import random
def a__ ( A__, A__ = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
lowerCAmelCase__ : List[str] =0.0_2
def a__ ( A__, A__ ):
SCREA... | 101 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _lowercase ( self ):
"""simple docstring"""
_lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
... | 5 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase =logging.get_logger(__name__)
__lowerCAmelCase ={
"asapp/sew-d-tiny-100k": "https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json",
# See all SE... | 333 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowercase = False
try:
_lowerca... | 5 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE):
lowerCamelCase__ ... | 500 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 5 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE_ = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
SCREAMING... | 517 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transfo... | 5 | 0 |
from math import pi, sqrt, tan
def UpperCamelCase (lowercase_: float ) -> List[str]:
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""" )
return 6 * side_length**2
def UpperCamelCase (lowercase_: float , lowercase_: float , lowerca... | 456 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 5 | 0 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-resear... | 608 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : Tuple = (DDPMScheduler,)
def _lowercase... | 5 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils imp... | 211 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
f... | 5 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Base... | 171 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-ba... | 5 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
fro... | 104 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Bl... | 5 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _lowercase ( _SCREAMING_SNAKE_CASE ):
@staticmethod
@abstractmethod
def UpperCamelCase ( lowerCamelCase__ : List[Any] ) -> Union[str, Any]:
"""simple docstring"""
raise Not... | 203 |
'''simple docstring'''
def A ():
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def A (__lowerCamelCase :List[Any] ):
_lowerCAmelCase = 1
_lowerCAmelCase = 2
while i * i <= n:
_lowerCAmelCase = 0
while ... | 5 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_SCREAMING_SNAKE_CASE )
class _UpperCAmelCase ( _SCREAMING_SNAKE_CASE ):
lowerCamelCase_ : str ... | 631 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
lowerCAmelCase__ : ... | 101 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_... | 5 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 333 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMAEConfig"]}
try:
if not is_torch... | 500 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"roberta-base": "https... | 517 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 5 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Optional[int] = logging.get_logger(__name__)
A_ : Tuple = {
'facebo... | 456 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMA... | 5 | 0 |
"""simple docstring"""
import functools
def a ( __snake_case : list[int], __snake_case : list[int] ):
'''simple docstring'''
if not isinstance(__lowerCamelCase, __lowerCamelCase ) or not all(isinstance(__lowerCamelCase, __lowerCamelCase ) for day in days ):
... | 608 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 | 0 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...im... | 211 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logge... | 5 | 0 |
from __future__ import annotations
from math import ceil, floor, sqrt
def UpperCamelCase( __UpperCamelCase : int = 2000000 ):
lowerCAmelCase_ : int = [0]
lowerCAmelCase_ : List[str] = 42
for idx in range(1 ,ceil(sqrt(target * 2 ) * 1.1 ) ):... | 171 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 | 0 |
"""simple docstring"""
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
UpperCamelCase = logging.get_logger(__name__)
def _lowerCamelCase ( UpperCAmelCa... | 104 |
'''simple docstring'''
import functools
def A (__lowerCamelCase :list[int] , __lowerCamelCase :list[int] ):
# Validation
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or not all(isinstance(__lowerCamelCase , __lowerCamelCase ) for day in days )... | 5 | 0 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__lowercase = logging.get_logger(__name__)
... | 203 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def A (__lowerCamelCase :List[Any] ):
_lowe... | 5 | 0 |
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